There are few major medical treatment decisions that are not, or should not, be influenced by a patient's understanding of his or her prognosis. Particularly among patients with advanced or life-limiting illness, decisions to pursue curative treatments and if so, how aggressively, whether to consider end-of-life options such as hastening death or physician assisted suicide, and even whether to sign a do-not- resuscitate order can be influenced by the patient's perception of whether his or her illness is curable or inevitably fatal - and if so, how quickly. Yet this research is often handicapped by the lack of a systematic tool for measuring a patient's understanding of his or her prognosis. Research focusing on prognostic understanding has been remarkably limited, and primarily comprised of studies that simply compare a patient's assessment of the curability of his or her disease to the physician's assessment of curability. Such studies fail to recognize the potential range of issues encompassed by the broader construct of prognostic understanding, such as life expectancy, potential utility of available interventions, and expectations regarding disease progression and functional decline. Thus, while the limited accuracy of physician assessments of prognosis are well documented, little attention has focused on how to best assess a patient's understanding of information related to prognosis. The present application seeks to fill this void by developing a systematic measure of prognostic understanding. Such an instrument has multiple potential uses, including facilitating physician discussions of prognosis (e.g., by identifying specific area of inaccuracy and/or misunderstanding) as well as research (e.g., analyzing the factors that influence patient decision-making). To accomplish these aims, we will first explore the phenomena of prognostic understanding using cognitive interviews of 15 experts drawn from oncology, palliative care, and psycho-oncology settings, as well as 15 patients with advanced cancer. A 2-stage open-coding process and Thematic Content Analysis framework will be used to identify critical themes, passages, and phrases, which will in turn then be used to develop a conceptual framework and a set of candidate items that might comprise a self-report scale. Candidate items will be reviewed by a second set of experts and cancer patients for clarity, thoroughness, and redundancy, and the revised items will be administered to 300 patients with advanced cancer, along with measures of psychological distress and social support. Classical test theory and item-response theory analyses will be used to identify items with the strongest psychometric properties. Physicians who care for these patients will also be asked to complete the same instrument, providing preliminary data on the accuracy of patient perceptions as well as variables that might correspond to these perceptions.